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An implementation pathway for price formation mechanisms in local electricity markets

Energy Reports 2025年 13卷 6384-6396页

作者： van de Water, P.R. Doumen, S.C. Campfens, J.K.E.K Wieczorek, A.J. Nguyen, P.H. Department of Electrical Engineering Eindhoven University of Technology PO Box 513 Eindhoven5600 MB Netherlands ENTRNCE International Koningstraat 28-1 Arnhem6811 DG Netherlands School of Industrial Engineering & Innovation Sciences Eindhoven University of Technology PO Box 513 Eindhoven5600 MB Netherlands Laboratory for Human Environment Relations in Urban Systems Institute of Environmental Engineering School of Architecture Civil and Environmental Engineering Ecole Polytechnique Federale de Lausanne Lausanne CH1015 Switzerland

The European Union is leading the shift towards a sustainable future, promoting the role of consumers as prosumers through renewable energy generation, energy communities, and Local Electricity Markets (LEMs). While LEMs have been studied in simulations and pilot projects, real-world adoption remains limited. This paper explores how three price formation mechanisms – system-determined, auction-based, and negotiation-based – can support LEM implementation, considering stakeholder preferences and LEM market conditions. The methodology considers the alignment with stakeholder preferences by applying Multi-Criteria Mapping, which maps the system operators, the public sector, market sector, cooperative sector, and academic sector. Analysis of stakeholder sectors shows a preference split between auction-based and system-determined mechanisms, both supporting fair and transparent price formation. System-determined mechanisms are additionally valued for their conceptual simplicity. However, concerns persist regarding their effectiveness under market power and low liquidity conditions in LEMs. A real-life case study simulation assesses the performance of all three price formation mechanisms using implementation pathway indicators identified through Multi-Criteria Mapping, notably the Market Concentration index and transactions per clearing interval. Combining stakeholder preferences and simulation outcomes, a four-phase implementation pathway is proposed as a framework for the large-scale deployment of LEMs. © 2025 The Authors

关键词： Mapping

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Typical antibiotic resistance genes and their association with driving factors in the coastal areas of Yangtze River Estuary

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environmental Science and Pollution Research 2024年第21期31卷 30440-30453页

作者： Xu, Qiuhong Liu, Shuguang Lou, Sha Tu, Junbiao Li, Xin Jin, Yuchen Yin, Wenjun Radnaeva, Larisa Dorzhievna Nikitina, Elena Makhinov, Aleksei Nikolavich Araruna, José Tavares Fedorova, Irina Viktorovna Department of Hydraulic Engineering College of Civil Engineering Tongji University Shanghai China Key Laboratory of Yangtze River Water Environment Ministry of Education Tongji University Shanghai China State Key Laboratory of Marine Geology Tongji University Shanghai China State Key Laboratory of Pollution Control and Resources Reuse College of Environmental Science and Engineering Tongji University Shanghai China Laboratory of Chemistry of Natural Systems Baikal Institute of Nature Management of Siberian Branch of the Russian Academy of Sciences Republic of Buryatia Russia Institute of Water and Ecology Problems Far East Branch Russian Academy of Sciences Khabarovsk Russia Pontifical Catholic University of Rio de Janeiro Rio de Janeiro Brazil Institute of Earth Sciences Saint Petersburg State University St Petersburg Russia

The massive use of antibiotics has led to the escalation of microbial resistance in aquatic environment, resulting in an increasing concern regarding antibiotic resistance genes (ARGs), posing a serious threat to ecological safety and human health. In this study, surface water samples were collected at eight sampling sites along the Yangtze River Estuary. The seasonal and spatial distribution patterns of 10 antibiotics and target genes in two major classes (sulfonamides and tetracyclines) were analyzed. The findings indicated a high prevalence of sulfonamide and tetracycline resistance genes along the Yangtze River Estuary. Kruskal–Wallis analysis revealed significant seasonal variations in the abundance of all target genes. The accumulation of antibiotic resistance genes in the coastal area of the Yangtze River Estuary can be attributed to the influence of urban instream runoff and the discharge of effluents from wastewater treatment plants. ANISOM analysis indicated significant seasonal differences in the microbial community structure. VPA showed that environmental factors contribute the most to ARG variation. PLS-PM demonstrate that environmental factors and microbial communities pose direct effect to ARG variation. Analysis of driving factors influencing ARGs in this study may shed new insights into the mechanism of the maintenance and propagation of ARGs. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Antibiotics

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The interdependent networked community resilience modeling environment(IN-CORE)

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Resilient Cities and Structures 2023年第2期2卷 57-66页

作者： John W.van de Lind Jamie Kruse Daniel T.Cox Paolo Gardoni Jong Sung Lee Jamie Padgett Therese P.McAllister Andre Barbosa Harvey Cutler Shannon Van Zandt Nathanael Rosenheim Christopher M.Navarro Elaina Sutley Sara Hamideh Harold H.Short Endowed Chair Professor and Co-Director Center of Excellence for Risk-Based Community Resilience PlanningDepartment of Civil and Environmental EngineeringColorado State UniversityFort CollinsCO80523USA Co-Director Center of Excellence for Risk-Based Community Resilience Planning and THCAS Distinguished ProfessorDepartment of EconomicsEast Carolina UniversityGreenvilleNC27858USA CH2M Hill Professor in Civil Engineering School of Civil and Construction EngineeringOregon State UniversityCorvallisOR97331USA Alfredo H.Ang Family Professor and Excellence Faculty Scholar Department of Civil and Environmental Engineeringand DirectorMid-America Earthquake(MAE)CenterUniversity of Illinois at Urbana-ChampaignChampaignIL61820USA Deputy Associate Director National Center for Supercomputing ApplicationsUniversity of Illinois at Urbana-ChampaignChampaignIL61820USA Professor and Chair Department of Civil and Environmental EngineeringRice UniversityHoustonTX77005USA Acting Chief Materials and Structural Systems DivisionNational Institute of Standards and TechnologyGaithersburgMD20899USA Professor Department of EconomicsColorado State UniversityFort CollinsCO80523USA Professor School of ArchitectureLandscape Architecture&Urban PlanningTexas A&M UniversityCollege StationTX77843USA Research Associate Professor Landscape Architecture&Urban PlanningTexas A&M UniversityCollege StationTX77843USA Lead Research Software Engineer National Center for Supercomputing ApplicationsUniversity of Illinois at Urbana-ChampaignChampaignIL61820USA Associate Professor and Associate Dean for Diversity EquityInclusionand BelongingDepartment of Civil and Environmental EngineeringUniversity of KansasLawrenceKansasUSA Associate Professor State University of New York-Stony BrookSchool of Marine and Atmospheric SciencesStony BrookNew YorkUSA

In 2015,the U.S National Institute of Standards and Technology(NIST)funded the Center of Excellence for Risk-Based Community Resilience Planning(CoE),a fourteen university-based consortium of almost 100 col-laborators,including faculty,students,post-doctoral scholars,and NIST *** paper highlights the scientific theory behind the state-of-the-art cloud platform being developed by the CoE-the Interdisciplinary Networked Community Resilience Modeling Environment(IN-CORE).IN-CORE enables communities,consul-tants,and researchers to set up complex interdependent models of an entire community consisting of people,businesses,social institutions,buildings,transportation networks,water networks,and electric power networks and to predict their performance and recovery to hazard scenario events,including uncertainty propagation through the chained *** modeling environment includes a detailed building inventory,hazard scenario models,building and infrastructure damage(fragility)and recovery functions,social science data-driven house-hold and business models,and computable general equilibrium(CGE)models of local *** important aspect of IN-CORE is the characterization of uncertainty and its propagation throughout the chained models of the *** illustrative examples of community testbeds are presented that look at hazard impacts and recovery on population,economics,physical services,and social *** overview of the IN-CORE technology and scientific implementation is described with a focus on four key community stability areas(CSA)that encompass an array of community resilience metrics(CRM)and support community resilience informed *** testbed within IN-CORE has been developed by a team of engineers,social scientists,urban planners,and *** models,begin with a community description,i.e.,people,businesses,buildings,infras-tructure,and progresses to the damage and loss of functions caused by a hazard scenario

关键词： IN-CORE Community Resilience Natural hazards Disasters Risk Uncertainty propagation Decision-support Mitigation Adaptation Tornado Tsunami Earthquake Hurricane

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Construction of a Probabilistic Model Describing Deterioration of Pumping Wells and Its Verification Using Actual Data

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Zairyo/Journal of the Society of Materials Science, Japan 2023年第3期72卷 168-173页

作者： Kawahara, Koki Nakano, Kosuke Kanekiyo, Hiroaki Kitaoka, Takafumi Kusumi, Harushige Graduate School of Science and Engineering Kansai University Yamate-cho Suita564-8680 Japan Central Japan Railway Company Meieki Nakamura-ku Nagoya450-6101 Japan Department of Civil Environment and Applied Systems Engineering Faculty of Environmental and Urban Engineering Kansai University Yamate-cho Suita564-8680 Japan

A probabilistic model is newly proposed for describing random deterioration of pumping wells, in consideration of application to efficient management of pumping wells using a concept of asset management procedure. First, introducing a health index for quantifying specific capacity, we formulate a differential equation describing mean deterioration of the helth index. Next, it is extended to a random differential equation, in which a Gaussian white noise is introduced for representing intensive fluctuation around the mean deterioration behavior, so that intensively random variation of the health index can be well reproduced. A probability distribution of the health index is then derived in an analytical form. Finally, the obtained probability distribution is compared with actual data of the health index for active eight pumping wells in Joyo area, Kyoto prefecture, Japan. It is clarified that the scatter of health index of actual pumping wells is quite well reproduced by the theoretically derived probability distribution from the newly proposed probabilistic model. © 2023 Society of Materials Science Japan. All rights reserved.

关键词： Deterioration

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Characterization of Autocovariance Parameters of Detrended Cone Tip Resistance from a Global CPT Database

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Journal of Geotechnical and Geoenvironmental engineering 2023年第10期149卷 04023090-04023090页

作者： Ching, Jianye Uzielli, Marco Phoon, Kok-Kwang Xu, Xiaojun Dept. of Civil Engineering National Taiwan Univ. Taipei10617 Taiwan Dept. of Civil and Environmental Engineering Univ. of Florence Firenze50139 Italy Information Systems Technology and Design/Architecture and Sustainable Design Singapore487372 Singapore

This paper compiles a cone penetration test (CPT) database, named Global-CPT/3/1196. It contains three CPT parameters (cone tip resistance, sleeve friction, and porewater pressure) from 1,196 CPT soundings taken at 59 sites worldwide. The spatially variable cone tip resistance corrected for porewater pressure (qt) soundings in the database are analyzed by a uniform procedure to characterize their autocovariance parameters consisting of a coefficient of variation, scale of fluctuation, smoothness, and hole effect. This is the first study that characterizes spatial variability based on a more complete set of three parameters: scale of fluctuation, smoothness, and hole effect. Previous studies were based on a single parameter (scale of fluctuation). The statistics of the autocovariance parameters and their inter-relationships are presented as a function of soil behavior type. These new statistics may be valuable for a future design founded on insufficient site investigation data: they can be used to obtain first-order estimates for the autocovariance parameters based on soil behavior type. Applications include data-driven site characterization and random finite-element analysis. © 2023 American Society of civil Engineers.

关键词： Database systems

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基于图像的深度学习降雨强度估计方法

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engineering 2023年第2期21卷 162-174,M0007页

作者：尹航郑飞飞段焕丰 Dragan Savic Zoran Kapelan College of Civil Engineering and Architecture Zhejiang UniversityHangzhou 310003China Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China KWR Water Research Institute Nieuwegein 3430 BBThe Netherlands Centre for Water Systems University of ExeterExeter EX44QFUK Faculty of Engineering and Built Environment Universiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Water Management Delft University of TechnologyDelft 2600 GAThe Netherlands

城市洪水是世界性的重大问题,造成巨大的经济损失,严重威胁公共安全。减轻其影响的一种有希望的方法是开发实时洪水风险管理系统;然而,由于缺乏高时空降雨数据,构建这样一个系统通常具有挑战性。虽然一些方法(即地面降雨站或雷达和卫星... 详细信息

城市洪水是世界性的重大问题,造成巨大的经济损失,严重威胁公共安全。减轻其影响的一种有希望的方法是开发实时洪水风险管理系统;然而,由于缺乏高时空降雨数据,构建这样一个系统通常具有挑战性。虽然一些方法(即地面降雨站或雷达和卫星技术)可用于测量和(或)预测降雨强度,但使用这些方法很难获得具有理想时空分辨率的准确降雨数据。本文提出了一种基于图像的深度学习模型来估计具有高时空分辨率的城市降雨强度。进一步来说,一种称为基于图像的降雨卷积神经网络(image-based rainfall CNN,irCNN)模型是使用从现有密集传感器(即智能手机或交通摄像头)收集的降雨图像及其相应的测量降雨强度值开发的。随后使用经过训练的irCNN模型根据传感器的降雨图像有效地估计降雨强度。分别利用合成降雨数据和真实降雨图像来探索irCNN在理论和实际模拟降雨强度方面的准确性。结果表明,irCNN模型提供的降雨量估计值的平均绝对百分比误差在13.5%~21.9%之间,超过了文献中其他最先进的建模技术的性能。更重要的是,所提出的irCNN的主要特点是它在有效获取高时空城市降雨数据方面成本较低。irCNN模型为估算城市降雨强度提供了一种有前景的替代方案,可以极大地促进城市实时洪水风险管理的发展。

关键词：卷积神经网络时空分辨率降雨强度深度学习 CNN 替代方案公共安全智能手机

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An interpretable (explainable) model based on machine learning and SHAP interpretation technique for mapping wind erosion hazard

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environmental Science and Pollution Research 2024年第56期31卷 64628-64643页

作者： Gholami, Hamid Darvishi, Ehsan Moradi, Navazollah Mohammadifar, Aliakbar Song, Yougui Li, Yue Niu, Baicheng Kaskaoutis, Dimitris Pradhan, Biswajeet Department of Natural Resources Engineering University of Hormozgan Hormozgan Bandar-Abbas Iran State Key Laboratory of Loess and Quaternary Geology Institute of Earth Environment Chinese Academy of Sciences 710061 Xi’an China Laoshan Laboratory Qingdao266061 China Academy of Plateau Science and Sustainability Xining810008 China College of Geography Qinghai Normal University Xining810008 China Dunhuang Gobi Desert Research Station Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences Lanzhou730000 China Department of Chemical Engineering University of Western Macedonia Kozani50100 Greece Centre for Advanced Modelling and Geospatial Information Systems School of Civil and Environmental Engineering University of Technology Sydney Sydney Australia Institute of Climate Change Universiti Kebangsaan Malaysia Bangi Malaysia Collaborative Scientist Institute for Environmental Research and Sustainable Development National Observatory of Athens P. Penteli Athens15236 Greece

Soil erosion by wind poses a significant threat to various regions across the globe, such as drylands in the Middle East and Iran. Wind erosion hazard maps can assist in identifying the regions of highest wind erosion risk and are a valuable tool for the mitigation of its destructive consequences. This study aims to map wind erosion hazards by developing an interpretable (explainable) model based on machine learning (ML) and Shapley additive exPlanation (SHAP) interpretation techniques. Four ML models, namely random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB), and quadratic discriminant analysis (QDA) were used. Thirteen features associated with wind erosion were mapped spatially and then subjected to a multivariate adaptive regression spline (MARS) feature selection algorithm, and then, tolerance coefficient (TC) and variance inflation factor (VIF) statistical tests were used to explore multicollinearity among the variables. MARS analysis shows that eight features consisting of elevation (or DEM), soil bulk density, precipitation, aspect, slope, soil sand content, vegetation cover (or NDVI), and lithology were the most effective for wind erosion, while no collinearity existed among these variables. The ML models were used for ranking the effective features, and the research introduces the application of an interpretable ML model for the interpretation of predictive model’s output. The ranking of effective features by RF—as the most typical ML model—revealed that elevation and soil bulk density were the two most important features. According to the area under the receiver operating characteristic curve (AUROC) (with a value > 90%) and precision-recall (PR) (with a value > 90%) curves, all four ML models performed with great accuracy. According to the PR curve, the SVM model performed slightly better than others, and its results revealed that 20.9%, 23%, and 16.6% of the total area in Hormozgan Province is characterized by moderate, hig

关键词： Support vector machines

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Grid-Aware On-Route Fast-Charging Infrastructure Planning for Battery Electric Bus with Equity Considerations: A Case Study in South King County

arXiv

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arXiv 2023年

作者： Zhao, Xinyi Zhao, Chaoyue Jia, Grace Department of Industrial & Systems Engineering University of Washington SeattleWA98195 United States Department of Civil & Environmental Engineering University of Washington SeattleWA98195 United States

The transition from traditional bus fleets to zero-emission ones necessitates the development of effective planning models for battery electric bus (BEB) charging infrastructure. On-route fast charging stations, distinct from on-base charging stations, present unique challenges related to safe operation and power supply capacity, making it difficult to control grid operational costs. This paper establishes a novel framework that integrates the bus route network and power network, which leverages the inter-dependency between both networks to optimize the planning outcomes of on-route BEB charging stations in South King County. The problem is formulated as a mixed-integer second-order cone programming model, aiming to minimize the overall planning cost, which includes investments in charging equipment, power facility, and grid operation. Furthermore, fairness measurements are incorporated into the planning process, allowing for the consideration of both horizontal transit equity and vertical transit equity based on different zone merging criteria within the county’s existing census tracts. The results of this planning model offer valuable insights into achieving both economic efficiency and social justice in the design of on-route charging facilities for BEBs in South King County. © 2023, CC BY.

关键词： Electric buses

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Testing Cellular Vehicle-to-Everything Communication Performance and Feasibility in Automated Vehicles *

Testing Cellular Vehicle-to-Everything Communication Perform...

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IEEE Symposium on Intelligent Vehicle

作者： Zhaohui Liang Jihun Han Xiaopeng Li Dominik Karbowski Chengyuan Ma Aymeric Rousseau Civil & Environmental Engineering Department University of Wisconsin Madison Madison WI USA Transportation and Power Systems (TAPS) Division The Argonne National Laboratory Lemont IL USA

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

Many studies have demonstrated the eco-driving capabilities of connected and automated vehicles (CAVs) to significantly enhance mobility systems. The majority of these studies have been conducted using simulations, which fail to capture the effects of practical uncertainties encountered in vehicle-to-anything (V2X) communications. In this paper, we investigated the performance of current cellular V2X (C-V2X) communications through systematic testing and provided a quantitative analysis of key performance indices (e.g., inter-packet gap and packet error rate) across various test scenarios. As one use case to demonstrate the benefits of C-V2X communication on the road, we tested the feasibility of eco-driving for a SAE level 3 (L3) automated vehicle (AV) communicating with a connected urban corridor capable of transmitting traffic light information (i.e., signal phase and timing). To achieve this, we implemented the eco-speed planning algorithm at a high-level in the AV control software system and ensured its interactions with other existing low-level control algorithms, as well as the C-V2X onboard unit. Finally, we experimentally demonstrated eco-driving of the L3 CAV on a scaled-down corridor with two signal-controlled intersections, revealing the AV’s ability to maintain smoother trajectories and avoid unnecessary stops compared to human-driven vehicles.

关键词： Wireless communication Uncertainty Systematics Statistical analysis Software algorithms Data models Trajectory

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Integration of Risk Sources and Risk Controls to SysML Requirements Diagrams With Application to Sustainable Aviation Fuels

Integration of Risk Sources and Risk Controls to SysML Requi...

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IEEE International Conference on Industrial engineering and engineering Management

作者： D. A. Johnson R.L. Wheeler M.C. Marcellin N. Moghadasi R.L. Altman T. L. Polmateer J.H. Lambert Dept. of Systems & Information Engineering Dept. of Civil & Environmental Engineering University of Virginia Charlottesville VA USA Commercial Aviation Alternative Fuels Initiative (Retired) USA

Sustainable aviation fuel (SAF) is a critical component of decarbonization of the aviation sector, is a “drop-in” technology solution that has gained the attention of stakeholders in the supply chains of jet fuel (growers to airport terminus). The inability of past work to fit SAF supply chains into a single strategy has led to the complexity of fuel demand and has left airports to address programmatic risks regarding cost, transportation, negotiations, schedule, and environmental conditions. This study proposes an innovative approach integrating the concepts of STAMP methodology and risk analysis into SysML requirements diagrams (systems Modeling Language), and demonstrates the new approach to evaluate the programmatic risk of SAF supply chains. This method supports risk assessment and management of business processes, contributing to awareness and preparedness of airport operators. The outcome of this research will contribute to a better understanding of the risk landscape and help stakeholders, particularly airport operators, navigate the challenges and uncertainties associated with adopting SAF. By tracking enterprise risks in a context of SysML requirements diagrams, airports can proactively implement mitigations, improve assurance protocols, optimize transportation logistics, streamline negotiations, enhance scheduling, and align with environmental considerations.

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